finalizing examples

docs/source/examples.rst

@@ -0,0 +1,23 @@
+Examples
+========
+
+ESM model
+~~~~~~~~~
+
+.. literalinclude:: ../../examples/esm_model.py
+   :language: python
+   :linenos:
+
+AA0 model
+~~~~~~~~~
+
+.. literalinclude:: ../../examples/aa0_model.py
+   :language: python
+   :linenos:
+
+3'UTR model
+~~~~~~~~~~~
+
+.. literalinclude:: ../../examples/3utr_model.py
+   :language: python
+   :linenos:

docs/source/index.rst

@@ -23,6 +23,8 @@ Query Parameters
 .. automodule:: ginkgo_ai_client.query_parameters
    :members:
 
-.. .. toctree::
-..    :maxdepth: 2
-..    :caption: Contents:
+.. toctree::
+   :maxdepth: 2
+   :caption: Contents:
+
+   examples

examples/3utr_model.py

@@ -1,4 +1,5 @@
-"""This runs embedding and masked inference queries on Ginkgo's 3'UTR language model."""
+"""In this example we compute embedding and run masked inference
+ on Ginkgo's 3'UTR language model."""
 
 from ginkgo_ai_client import (
     GinkgoAIClient,

examples/aa0_model.py

@@ -1,23 +1,26 @@
+"""In this example we compute embedding and run masked inference
+ on Ginkgo's AA0 protein language model."""
+
 from ginkgo_ai_client import (
     GinkgoAIClient,
-    three_utr_mean_embedding_params,
-    three_utr_masked_inference_params,
+    aa0_mean_embedding_params,
+    aa0_masked_inference_params,
 )
 
 client = GinkgoAIClient()
 
 # Simple query for embedding computation
-prediction = client.query(three_utr_mean_embedding_params("ATTGCG"))
+prediction = client.query(aa0_mean_embedding_params("ATTGCG"))
 # prediction["embedding"] == [1.05, -2.34, ...]
 
 
 # Simple query for masked inference
-prediction = client.query(three_utr_masked_inference_params("ATT<mask>TAC"))
+prediction = client.query(aa0_masked_inference_params("ATT<mask>TAC"))
 
 queries = [
-    three_utr_mean_embedding_params("AGCGC"),
-    three_utr_mean_embedding_params("ATTGCG"),
-    three_utr_mean_embedding_params("TACCGCA"),
+    aa0_mean_embedding_params("AGCGC"),
+    aa0_mean_embedding_params("ATTGCG"),
+    aa0_mean_embedding_params("TACCGCA"),
 ]
 predictions = client.batch_query(queries)
 

examples/esm_model.py

@@ -1,25 +1,26 @@
-"""This runs embedding and masked inference queries on Ginkgo's 3'UTR language model."""
+"""In this example we compute embedding and run masked inference
+ on the ESM2 language model."""
 
 from ginkgo_ai_client import (
     GinkgoAIClient,
-    aa0_mean_embedding_params,
-    aa0_masked_inference_params,
+    esm_mean_embedding_params,
+    esm_masked_inference_params,
 )
 
 client = GinkgoAIClient()
 
 # Simple query for embedding computation
-prediction = client.query(aa0_mean_embedding_params("MLYLRRL"))
+prediction = client.query(esm_mean_embedding_params("MLYLRRL"))
 # prediction["embedding"] == [1.05, -2.34, ...]
 
 
 # Simple query for masked inference
-prediction = client.query(aa0_masked_inference_params("MLY<mask>RRL"))
+prediction = client.query(esm_masked_inference_params("MLY<mask>RRL"))
 
 queries = [
-    aa0_mean_embedding_params("MLYLRRL"),
-    aa0_mean_embedding_params("MLYRRL"),
-    aa0_mean_embedding_params("MLYLLRRL"),
+    esm_mean_embedding_params("MLYLRRL"),
+    esm_mean_embedding_params("MLYRRL"),
+    esm_mean_embedding_params("MLYLLRRL"),
 ]
 predictions = client.batch_query(queries)